Statistical Methods for Neural Mechanisms Mediating Cognitive System in Mental Health Research

心理健康研究中调节认知系统的神经机制的统计方法

• 批准号: 9278065
• 负责人: SEONJOO LEE
• 金额: $ 13.14万
• 依托单位: NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-30 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9278065
• 关键词: Adult; Affect; Age; Age-associated memory impairment; Aging; Alzheimer' s Disease; Applications Grants; Award; Biological Neural Networks; Biometry; Brain; Brain imaging; Cognition; Cognition Disorders; Cognitive; Cognitive aging; Data; Data Set; Data Sources; Development; Early Diagnosis; Elderly; Episodic memory; Functional Magnetic Resonance Imaging; Goals; Heterogeneity; Image; Impaired cognition; Liquid substance; Machine Learning; Magnetic Resonance Imaging; Measurement; Measures; Mediating; Mediation; Mediator of activation protein; Mental Health; Mental disorders; Mentors; Methods; Modality; Modeling; Multicenter Studies; Nerve Degeneration; Neurosciences; Pathology; Pattern; Performance; Psychiatry; Psychopathology; Research; Role; Speed; Statistical Data Interpretation; Statistical Methods; Structure; System; Techniques; Testing; Training; age effect; age related; analytical tool; brain volume; career; cerebral atrophy; cognitive ability; cognitive change; cognitive system; cognitive task; cognitive testing; imaging study; method development; mild cognitive impairment; multimodality; neuroimaging; neuromechanism; normal aging; novel; pathological aging; public health relevance; relating to nervous system; research and development; tool

 DESCRIPTION (provided by applicant): Psychiatric disorders, as well as normal aging, are often associated with a wide range of cognitive changes. Recent developments in neuroscience, particularly multimodal neuroimaging techniques, can provide better understanding of neural mechanisms that underlie these changes. Mediation analysis is a popularly used statistical method to investigate neural mechanisms. However, existing statistical methods were not designed to accommodate such large-scale, multi-dimensional, and complicated data in mediation analysis. The overarching aim of my K01 Mentored Research Development Award is to acquire training that will allow me to pursue a line of mental health research related to cognition and to develop novel statistical methods to support the emerging research in cognitive neuroimaging and mental health. I propose to receive training in: 1) cognition and its relationship with aging and psychopathology; 2) neural basis in cognition and multimodal neuroimaging; 3) functional mediation and selective mediation analysis. This will provide me with the tools to conduct research that will fill significant gaps in the statistical analyses on cognitive neuroimaging, particularly focusing on aging and neurodegeneration-associated cognitive decline: First, I propose to review and develop analytic tools to examine how aging and psychopathology affect cognitive system constructs. Understanding the patterns of age-related differences in each of these cognitive constructs and the possible heterogeneity related to the psychopathology is of great importance. I will test nonlinearity and heterogeneity in the latent cognitive constructs using two independent large data. Second, I will develop and examine activation networks (reference ability neural networks (RANNs)) associated with each of the cognitive constructs. Although it is critical to understand underlying neural networks of cognition, there are many unsolved problems in investigating the presence or structure of RANNs. I will develop a method to derive underlying networks, find RANNs taking into account possible spatial overlap among RANNs, and investigate the relationship between RANNs expression and performance on the concomitant cognitive constructs. Third, I will develop selective mediation analyses to examine the relationship between imaged neural substrates of aging and psychiatric disorder, such as regional volume loss, and cognitive decline and test if the different imaged brain modalities selectively mediate cognitive aging by influencing the expression of cognitive ability constructs. In totality, this training and research will inform hypotheses for an R01 grant application to be submitted in Year 4 of the award period. While to date I have exemplified a productive research career in biostatistics and psychiatry, I need substantially more training for successful completion of the research proposed in this application and to make a lasting contribution to the field of mental health.

 描述(由申请人提供)：精神障碍，以及正常的衰老，通常与广泛的认知变化有关。神经科学的最新发展，特别是多模式神经成像技术，可以更好地理解这些变化背后的神经机制。中介分析是研究神经机制的一种常用的统计方法。然而，现有的统计方法并不适合在中介分析中容纳如此大规模、多维和复杂的数据。我的K01指导研究发展奖的总体目标是获得培训，使我能够从事一系列与认知相关的心理健康研究，并开发新的统计方法，以支持认知神经成像和心理健康方面的新兴研究。我建议接受以下方面的培训：1)认知及其与衰老和精神病理学的关系；2)认知的神经基础和多通道神经成像；3)功能调节和选择性调节分析。这将为我提供进行研究的工具，这些研究将填补认知神经成像统计分析中的重大空白，特别是关注与衰老和神经退化相关的认知衰退：首先，我建议回顾和开发分析工具，以研究衰老和精神病理学如何影响认知系统结构。了解这些认知结构中与年龄相关的差异的模式以及与精神病理学相关的可能的异质性是非常重要的。我将使用两个独立的大数据来检验潜在认知结构中的非线性和异质性。其次，我将开发和研究与每个认知结构相关的激活网络(参考能力神经网络(RAN))。尽管了解潜在的认知神经网络是至关重要的，但在研究RAN的存在或结构方面仍有许多悬而未决的问题。我将开发一种方法来推导潜在的网络，在考虑到RAN之间可能的空间重叠的情况下找到RAN，并研究RAN的表达与伴随认知结构上的表现之间的关系。第三，我将开展选择性中介分析，以考察衰老的成像神经底物与精神障碍之间的关系，如局部体积丧失和认知能力下降，并测试不同的成像脑形态是否通过影响认知能力结构的表达选择性地中介认知衰老。总的来说，这项培训和研究将为将在授权期第四年提交的R01赠款申请提供假设。虽然到目前为止，我在生物统计学和精神病学方面的研究生涯卓有成效，但我需要更多的培训，才能成功完成这项申请中提出的研究，并为心理健康领域做出持久的贡献。